Postdoctoral Fellow in Electromechanical Engineering (Ghent University)

Department: TW08 – Department of Electromechanical, Systems and Metal Engineering Institution: Ghent University Degree Required: M.Sc. in Mechanical Engineering, Mechatronics, or related engineering fields Occupancy Rate: 100% Vacancy Type: Research Staff Application Deadline: 14 March 2026, 23:59 About Ghent University Ghent University employs over 15,000 people and is actively involved in education, research, management, and technical and social service provision. With 11 faculties and more than 85 departments, the university offers state-of-the-art programs and a dynamic, inclusive work environment. Project Overview – Dynamic Design Lab & CausAICA The Dynamic Design Lab focuses on modelling, control, and optimization for mechatronic systems, industrial robots, and processes. This PhD is part of the Flanders Make SBO project CausAICA, which aims to develop next-generation causal reasoning frameworks for explainable and trustworthy diagnosis of complex industrial systems. Key features of the research: Hybrid modelling: integrates physics-based knowledge, experimental data, and probabilistic reasoning Focus: fault diagnosis and root-cause identification for a web-winding machine Applications: extendable to wind turbines, motors, and other industrial mechatronic setups Project goals include developing causal AI methodologies that are accurate, physically interpretable, and uncertainty-aware. Responsibilities Develop scalable causal discovery and inference methods for mechatronic systems Validate causal structures and root causes against experimental and simulation fault fingerprints Seek industrial and societal impact of methodologies Present research at conferences and in journals Collaborate with researchers within and outside the research group Candidate Profile Master’s degree in Mechanical/Electromechanical Engineering, Mechatronics, or related fields Experience in system identification and modelling of mechatronic systems Proficient in Python programming Knowledge of physics-based and data-driven modelling Familiarity with mechatronic hardware and software Strong foundation in probability, statistics, Bayesian modelling, uncertainty quantification, and causal inference Creative, team-oriented, results-driven, and able to work in multidisciplinary contexts Excellent communication skills in English Willingness to extend networks and discuss technical matters What We Offer Full-time doctoral fellowship (initial 12 months, extendable to 48 months) Earliest start date: 1 April 2026 Fellowship: 100% of net salary of an AAP member (tax-free), adjusted for family status and seniority Access to state-of-the-art tools, facilities, and Flanders Make industry network Opportunity to improve expertise in machine learning, (probabilistic) modelling, system identification, and numerical optimization Benefits: 36 days annual leave + bridge days, bicycle allowance, eco vouchers, and training opportunities Application Procedure Send your CV, copy of diploma (if already obtained), and motivation letter to: ???? annelies.coene@ugent.be Include ‘CAUSAL PHD’ in the email subject. Deadline: 14 March 2026 Selected candidates will be invited for an online interview. Late applications will not be accepted. Equal Opportunities Ghent University promotes diversity and equal opportunities. Applicants from all backgrounds are encouraged to apply. For further information, contact: Annelies Coene – annelies.coene@ugent.be, +32(0)9/264 57 04 If you apply for this position please say you saw it on Academicoxy

Department: TW08 – Department of Electromechanical, Systems and Metal Engineering
Institution: Ghent University
Degree Required: M.Sc. in Mechanical Engineering, Mechatronics, or related engineering fields
Occupancy Rate: 100%
Vacancy Type: Research Staff
Application Deadline: 14 March 2026, 23:59

About Ghent University

Ghent University employs over 15,000 people and is actively involved in education, research, management, and technical and social service provision. With 11 faculties and more than 85 departments, the university offers state-of-the-art programs and a dynamic, inclusive work environment.

Project Overview – Dynamic Design Lab & CausAICA

The Dynamic Design Lab focuses on modelling, control, and optimization for mechatronic systems, industrial robots, and processes.

This PhD is part of the Flanders Make SBO project CausAICA, which aims to develop next-generation causal reasoning frameworks for explainable and trustworthy diagnosis of complex industrial systems.

Key features of the research:

Hybrid modelling: integrates physics-based knowledge, experimental data, and probabilistic reasoning
Focus: fault diagnosis and root-cause identification for a web-winding machine
Applications: extendable to wind turbines, motors, and other industrial mechatronic setups

Project goals include developing causal AI methodologies that are accurate, physically interpretable, and uncertainty-aware.

Responsibilities

Develop scalable causal discovery and inference methods for mechatronic systems
Validate causal structures and root causes against experimental and simulation fault fingerprints
Seek industrial and societal impact of methodologies
Present research at conferences and in journals
Collaborate with researchers within and outside the research group

Candidate Profile

Master’s degree in Mechanical/Electromechanical Engineering, Mechatronics, or related fields
Experience in system identification and modelling of mechatronic systems
Proficient in Python programming
Knowledge of physics-based and data-driven modelling
Familiarity with mechatronic hardware and software
Strong foundation in probability, statistics, Bayesian modelling, uncertainty quantification, and causal inference
Creative, team-oriented, results-driven, and able to work in multidisciplinary contexts
Excellent communication skills in English
Willingness to extend networks and discuss technical matters

What We Offer

Full-time doctoral fellowship (initial 12 months, extendable to 48 months)
Earliest start date: 1 April 2026
Fellowship: 100% of net salary of an AAP member (tax-free), adjusted for family status and seniority
Access to state-of-the-art tools, facilities, and Flanders Make industry network
Opportunity to improve expertise in machine learning, (probabilistic) modelling, system identification, and numerical optimization
Benefits: 36 days annual leave + bridge days, bicycle allowance, eco vouchers, and training opportunities

Application Procedure

Send your CV, copy of diploma (if already obtained), and motivation letter to:
???? annelies.coene@ugent.be
Include ‘CAUSAL PHD’ in the email subject.

Deadline: 14 March 2026

Selected candidates will be invited for an online interview. Late applications will not be accepted.